The technology disclosed herein generally relates to flight management systems for airplanes and, more particularly, relates to techniques for computing predicted flight profile and associated trip prediction parameters in a flight management system.
A flight management system (hereinafter “FMS” when used as an adjective) installed in the flight deck of a modern airplane performs various flight critical functions such as navigation, guidance, flight planning, datalink and performance. For the performance function, the flight management system has various internal algorithms (hereinafter “performance algorithms”) that utilize aerodynamic and propulsion performance data (hereinafter “performance data”) stored in a performance database to compute the predicted flight profile and the associated trip prediction parameters such as speed, altitude, estimated time of arrival (ETA) and predicted fuel consumption.
Many airlines are looking to enhance fuel performance through extensive on-ground flight/fuel planning to reflect the true fuel flow and drag characteristics of individual airplanes. It is known for a manufacturer of a particular model of an airplane to install or provide a baseline performance database onboard each airplane. As used herein, the term “baseline performance database” refers to an original performance database, generated by an airplane manufacturer, that is common to a multiplicity of airplanes of a particular model. Typically airplanes of a particular model have the same baseline performance database stored in memory disposed in or associated with the flight management system. Therefore, if two airlines have airplanes of the same model in their respective fleets, the baseline performance database used by one airline will be the same as that used by the other airline.
Currently, a flight management system has predefined baseline performance data that is used for various computations such as lateral and vertical trajectories, estimated fuel burn at various waypoints, estimated weights at various waypoints, etc. This predefined baseline performance data is consistent across an entire type of aircraft. For instance, all 737-800 airframes with winglets and 28K engines and of similar age are assumed to have the exact same performance characteristics. Currently, things like manufacturing tolerances are not accounted for in the predefined baseline performance data but have a real, and unique, impact to each specific airframe.
The typical baseline performance database in a flight management system contains aerodynamics and propulsion data that is representative of airplane characteristics determined during a series of flight tests that usually occur in a controlled environment with precise onboard measurement equipment before the airplane is delivered to a customer airline. It is assumed herein that a baseline performance database generated by testing an individual airplane of a particular model is equally applicable to all airplanes of the same model, in which case that same baseline performance database can be loaded into the flight management systems of all airplanes of that model. Such a widely employed baseline performance database is rarely updated once delivered to the airline due to large costs associated with build, test, and certification.
However, over the course of time the characteristics of individual airplanes of the same model may vary due to changes to the airplane's aerodynamic and propulsion characteristics. For example, due to changes to an airframe, such as repairs, addition or removal of antennas, configuration changes, etc., and engine deterioration, the airplane fuel flow and drag characteristics (e.g., a fuel factor and a drag coefficient respectively) may change over time. As a result, the performance algorithms and the baseline performance data may deviate from the actual airplane performance over time as an individual airplane continues to operate in service.
One solution in use today is that some flight management systems have a global, manual adjustment to the overall drag and overall fuel flow of the predefined baseline performance data. This solution allows the user to globally add a percent error to the flight management system's predefined drag data and fuel flow data. For instance, if the user enters a drag error of 4.2, the flight management system will now calculate all drag values as predefined_drag*1.042 (the asterisk indicates multiplication). This 4.2% additional drag component is added to all drag computations, regardless of where in the flight envelope the drag calculation takes place. This same issue exists with the global fuel flow adjustment. Additionally, users of the flight management system must develop their own methods for measuring the differences between the predefined baseline performance data and the actual performance and develop methods to extrapolate these differences into respective single drag and fuel flow error percentages. The largest drawback to the existing solution is that this is a global adjustment to all calculations and users must develop their own methods and schedules for updating the adjustments in the flight management system to maintain accurate airplane performance data.
The fleet of an airline may comprise a multiplicity of airplanes of the same model wherein each individual airline of that model in the fleet may have unique airplane characteristics. In this situation, an airline may want to update the performance database onboard each airplane in a timely and efficient manner to more accurately reflect the true characteristics of each airplane in its fleet. For example, individual airplanes may have fuel efficiency and drag characteristics which change differently over time.
In an alternative example, two airlines may have the same basic model of airplane in their respective fleets except that one airline has made modifications to the airplanes of that model which are absent from the airplanes of that model operated by the other airline. In this situation, the airline operating the modified airplanes may want to provide the same updated performance data for use by the flight management systems onboard all of the modified airplanes of the same model.
Thus it would be advantageous to provide an improved flight management system that uses up-to-date (i.e., most accurate) information that takes into account the variable actual characteristics of individual airplanes when computing a predicted flight profile and associated trip prediction parameters for that airplane.